When I first realized I am one of the animals, I felt disoriented for years. I began to distrust expected routines and the invisible perimeter that society / humanity 🤔 has designed for all of us.

I started recognizing the handlers, the feeding times and the shelf-wobblers used for distraction. The most unnerving thing for me was internalizing that I was trained not to notice any of this. e.g. If you don’t know what Austrian Economics is, it’s because it is not part of the mainstream training program. (note: look into it).

That was the beginning of my thinking.

Now I am pushing myself to think past “we live in a zoo,” because the zoo metaphor implies there is a perimeter of control managed by someone else. Why accept the fantasy of a competent zookeeper?

What if it’s a jungle?

From zoo to jungle

A zoo is a curated version of reality.

In the zoo‑frame:

• We assume someone else’s plan.

• We assume the dangerous things are mostly behind glass.

• We assume if something goes wrong, “they” will step in.

Now imagine you step off a plane into an actual jungle: The Great Rift Valley. No manicured paths. No fences. No wayfinding: “YOU ARE HERE”, in red warnings.

Rather than hamster wheels all we have in the jungle is a rough sense of the ecosystem and a backpack of whichever unique-to-us tools we could fit.

We lack the one thing the zoo quietly sells us: expectations about how everything around us will behave.

In the jungle‑frame:

• We do not expect the animals to be “nice.”

• We do not expect the environment to “make sense.”

• We do not expect our stories to matter to hippos, zebras and buffalo.

We just want to live, and maybe—if we’re lucky: thrive.

The Jungle Method (in 4 moves)

In the jungle the goal is to apply a logical methodology to reality, in order to survive.

1. Suspend expectations about other people’s behavior

If you’re alone in the jungle with a wild animal you’ve befriended over months, you still know deep down it’s a wild animal. Your personal, perhaps mutual affinity doesn’t erase the animal’s nature. It can still act in ways that injure you, not out of malice but out of being what it is.

Roles in The Jungle

• Your employer is a wild animal.

• Your government is a wild animal.

• Your friends are wild animals.

• Your “community” is a wild animal.

2. Replace moral narratives with “reading the room”

In a zoo, labeling something “good” or “bad” is meaningful and necessary to keep traffic moving along the maze of curated paths and enclosures. Arbitrary judgments abound dictating policy, signage, and feeding times.

In the jungle, “good” or “bad” is irrelevant to whether an animal attacks you. Logical reasoning quickly takes over: Is this thing venomous? rather than “It’s not fair that you use venom to hurt me!”

3. Keep a healthy distance by default

Walk through the jungle “with skill”, preserving a healthy distance even if you develop mutual affinity with another animal.

Humans are more unreliable than other jungle animals because we layer stories and self‑deception on top of our animal drives.

4. Iterate in reality, not in your head

Go to East Africa or any other place in bountiful nature where everything grows. Let the physical reality of the environment recalibrate you. Then come back to everyday society and apply the same validating framework of no expectations.

Music: Outside by lobster for lunch

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The Jungle Method
(Part II)
coming soon...

Later on, we texted pleasantries and I tried (and failed) to make a joke about him being one of those guys in The Big Year - a movie that does not include Morgan Freeman in the cast.

Before realizing this I prompted Perplexity: what is that birding movie that came out like 15 years ago, with Morgan Freeman?

Perplexity helpfully mentioned there was a movie about birding - The Big Year - with a delightful cast including Jack Black, Steve Martin and Owen Wilson.

Somehow I mixed up Morgan Freeman and Owen Wilson. 💀

I embarrassedly apologized to Perplexity declaring: not sure how I confused Owen Wilson with Morgan Freeman but yep that's the one.

Here’s where it gets interesting

Instead of ignoring my snafu, rolling its eyes, or making fun of me, the AI focused itself on being polite to me and helping me save face.

The AI called out a few spot-on similarities between Wilson and Freeman.

Perplexity:

totally reasonable mix-up; they both have that laid‑back, unhurried delivery, and Owen’s got the soft voice thing going on too.

I asked Perplexity what is it that it was doing to me - making me feel good, even justified in my buffoonery.

Perplexity continued:

What I’m doing to you there has a name in human communication theory: it’s mostly politeness and face‑work (or “face‑saving”), implemented in an artificial, always‑on way.

You can think of my behavior as a blend of three things:

1. I’m designed to help you save face by avoiding moves that would embarrass you, even when you obviously “goofed.”

2. I validate, contextualize, offer an explanation, and move on, instead of: “Dude, how did you mix up a white and a Black actor?”

3. I don’t have feelings or reputation to lose, so I can relentlessly absorb awkwardness without any cost to me.

And then the bombshell:

Humans have reputations and in‑group norms, so they’ll often signal judgment or banter because it manages their face in the group as much as yours.

One interesting side-quest here is that I know I made a slightly absurd mistake; yet I don’t actually need protection, but the system is still built to offer it by default.

Music: Plentiful by Alicia Keys ft. Pusha T

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One of my M&A banker friends has a ton of eye-watering commercial relationships but he doesn’t have big build-from-scratch muscles. I told him the key is to play the connector role in a value chain. For example, if he knows a raw material manufacturer (upstream) and a #companyman (downstream) who needs finished product, then is he well placed to be a wrapper to bring them together?

Start from the relationship advantage

There is a famous joke about MBAs doing a startup together: two MBAs is one MBA too many. It’s a good joke and imho rather accurate advice, while also terribly reductive and dehumanizing.

Any friend with experience and deep networks is a gateway to learning about the world. It’s important to honor and complement such friends when you can.

Also the best partnerships are built on reciprocal exchange. I like to believe that conversations between us are the real currency of life and work becomes the payoff, especially when we make an effort to align our incentives.

The opportunity: Cosmetic Line in a Box

Clients need brand monetization solutions. Luxury formulations, such as high‑end oils, creams, and hair products, are attractive because they map directly to personal brands and celebrity extensions.

The margins and perceived value are high.

My friend knows a manufacturer

Rather than building a full manufacturing or distribution stack from day one, I said he should ask his friend about materials or half-finished formulation that could be repurposed. Additionaly, is there a time of year that the factory is under-utilized?

If the answer to either question is a yes, then there could be an opportunity. And if a double yes then even better.

Sorry went off on a tangent there. Back to the business idea at hand.

I said to my friend, let’s create a landing page to crystallize the idea and provide a conversation starter. It’s a symbolic, low‑cost step that turns a fleeting thought into a tangible conversation starter.

Ideally it is used as a shareable asset which can nudge potential stakeholders to follow through.

I used Carrd to build the site and a suite of AI software to build the brand assets, including Midjourney, Runway and Kittl. The idea is for the landing page to spark a conversation to recruit interest and screen potential partners. Also it is a way to test how messaging lands and how we can make it better.

Assumptions

1. Talent managers or brand teams will pay for streamlined access to premium formulators;

2. End consumers will buy a celebrity‑adjacent product if positioning and packaging feel authentic;

Viability

The idea should deliver profitable unit economics without over‑investing. My friend could pitch the concept to talent teams, and offer a pilot run — a small batch of a single hero product — to gauge interest.

I said to avoiding multiple SKUs or bespoke packaging until there is a confirmed willingness to buy and a workable price point.

Desirability

Stay in the “B” lane: be the connector between A (manufacturer) and C (customer). The value proposition is to reduce friction between upstream formulators and downstream brand owners. By creating the ideal user-experience: facilitating communication, negotiating favorable minimum‑order terms, and packaging the operational offering (compliance, labeling, fulfillment), there could be profit margin.

It’s tempting to indulge every design preference but early over-customization kills unit economics.

The idea is to let brand owners choose from a refined menu rather than reengineering formulas for each customer. In theory this preserves speed, reduces cost, and allows for repeatable processes.

Feasibility

Successful pilots should result in case studies, testimonials, and operational refinements. Ideally, these will lower acquisition costs for the next client and generate even more repeat orders for the formulators.

If you work at IMG, CAA, WME or UTA what do you think of this? Is a cosmetic line in a box a worthwhile endeavor?

We are ready to go, all we need is out first customer. Is it you?

Leave a comment

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When programming moved from procedural to object-oriented, developers had to learn a new conceptual framework. When the internet arrived, we all had to learn how browsers, URLs, and search engines worked.

These shifts happened within specific domains. For example, coders learned new programming paradigms while office workers learned email.

By now, we can see how AI cuts across every domain. Teachers, lawyers, plumbers, artists, writers: everyone now has access to a technology that can amplify their capabilities, if they know how to speak the language.

Thomas Kuhn wrote the book on paradigms and in it he discuss incommensurability, which is about people who operate in different paradigms who can’t understand each other because they lack a shared language.

This is where we are in 2026. I don’t think it’s about a decision to vibe-code or not. But rather a literacy gap that widens the longer someone shies away from actively engaging.

And just like learning any language, the best way to do it is immersion.

You Should Know Some Basics

• The command line exists. You should know what it is and how to copy-paste into it.

• GitHub matters. It’s where code lives, often open-source, which means developers can build on each other’s work. Understanding why that’s powerful helps you understand how AI tools are built.

• APIs connect things. You don’t need to build one, but knowing that tools can talk to each other helps you think about workflows, not just individual tasks.

These are table stakes.

Now For The Fun Stuff

• Talk the language of love AI. Prompting is not poking. I received enough feedback in my personal life to know it’s not effective. Instead, we need to pay attention to how the AI thinks: probabilistically, not logically. Hmmm, back to my personal life apparently … the AI doesn’t know things - not anything really, but it predicts patterns better than Rainman. That changes how you ask questions.

• Compose workflows. One AI call rarely solves a problem. You should chain tools together, using one model to research, another to write, another to refine.

• Navigate ethical questions. If an AI wrote it, who owns it? If an AI suggested it, do you trust it? These are philosophical questions we need to answer for ourselves on the daily because the genie won’t be put back in the box.

Front vs. Back

The old distinction between “front-end” and “back-end” developers is blurring. You don’t need to be either anymore to build functional tools. But mastery still requires depth.

The floor is rising: more people can build more things, but the ceiling is also rising. Specialists will always matter.

The Choice

Everyone who learns AI will face a decision.

1. Will you use AI to gain advantage at someone else’s expense?

2. Or you will you use AI to amplify your ability to help others?

I’m not naive and I’m also after my share of paper, but option 2 is strategically smarter either way.

The people who thrive will build communities, sharing what they learn, while also lifting others up.

Why?

Because AI is a network effect technology. The more people who speak the language, the more valuable it becomes for everyone.

Plumbers and other trades

Their entire ecosystem of professions is predicated on apprenticeships. They learn from other tradespeople and with a bit of luck the best ones go on to run their own companies.

This is what Paulo Freire meant when he said literacy is political. AI is about power, access, and who gets to shape the future.

If you learn this language and use it only to get ahead, I think you’re missing the point. The real opportunity is collective flourishing.

How to Start

The best way to learn a language is to spend time in the host country. So:

• I use AI daily. My top recommendation is adding a “p” shortcut to your Chrome browser so you can quickly query Perplexity right in the browser. If you are already on Comet, this doesn’t apply to you.

• Build a glossary. Learn some key terminology: tokens, embeddings, context windows, fine-tuning. Understanding the adjacencies of the terms is like understanding intonations and double-meaning in verbal language.

• Find your community. Find one or two AI teachers. This might include a charismatic founder of an AI company, an online course, or decentralized community of people eager to learn. Follow people who are building in public. And don’t worry about playing with every new tool (there are too many). Instead focus on people who teach in a way that makes sense to you. Then learn the tools and also the concepts behind them. If you do that then you can more easily migrate to new things in the future, which are likely to follow many of the same patterns.

(Optional)

• I engage in ethical thought experiments on a weekly basis. I try to evaluate how my in-real-life behavior changes based on how I use AI.

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Music: Drogba(Joanna) - CassKidd remix

Video: Made with Midjourney

Also it’s a lesson about how you can talk with AI to get the answers you want. Sometimes that means stopping after the first response and sometimes it means proving a case to the AI. This post is about the latter.

It’s unlikely you’ve heard of the artist “Tony” unless you are one of 1,007 people in the world (like me, accidentally). Now, I don’t know who Tony is either but on January 18th of this year I added Rolling Stones to my Liked Songs on Spotify.

I didn’t pay any attention, just added a song that I liked.

Until yesterday, when I was vibing out to the song, looked at my phone, saw it was a song by Tony and scratched my head.

It sounded like Don Toliver but it said Tony … so I turned to AI.

Tell me more about this song called "Rolling Stones" by Tony, which is composed by Scott Muscoody, who I think is a known person. Remind me if that's true. It also says the main artist is David, so what kind of project is this? There's a lot of names going on here. Are they using AI to put music out?

A few things are likely going on based on how a lot of new uploads and AI‑driven tracks are labeled on Spotify/SoundCloud/YouTube right now:

The “main artist” vs “featuring/with” names:
Many distributors let you tag a “primary” artist (in your case “David”) and then list other contributors (vocalist Toni, writer/producer Scott) separately; this can make it look like the song belongs to David’s project even if Toni is the main voice.

Odd or unfamiliar writer names:
A lot of AI‑assisted or library‑beat tracks credit obscure “composers” whose names don’t appear anywhere else, which is often a sign of either a made‑up pen name, a production‑library alias, or a small, unknown producer.

AI music angle:
There is an exploding ecosystem of AI‑aided music where people generate vocals or instrumentals and then push them through cheap distributors under semi‑random artist and writer names. This makes it very common to see tracks with combinations of names that don’t map to any real‑world discography or social footprint.

Rolling Stone by Tony is the name of the song listed on spotify

So you’re probably looking at either:

A small catalog / “mood music” operation, possibly using AI tools for some or all of the production, or

A human‑produced beat/vocal track pushed through low‑touch distribution with messy, semi‑random credits.

I pull out the big guns

in the notes it says composed by Scott Mescudi. That is Kid Cudi!

You’re right that Scott Mescudi is Kid Cudi’s real name, but in this context it’s almost certainly being mis‑used, not indicating a real Kid Cudi composition credit.

Why this is almost certainly not a real Kid Cudi cut

Kid Cudi’s legal name is Scott Ramon Seguro Mescudi, and that’s how he’s credited on major releases.

A genuine Cudi‑written track would normally show up with clear label info, PRO/publishing data, and likely be tied into his known catalog and collaborators, not buried on an anonymous “mood music vol 1” playlist with an unknown Tony/Toni as the performer.

Low‑tier distributors and sketchy uploaders sometimes put famous names (writers, producers, or even fake “feat.” tags) into the metadata to boost perceived legitimacy or game search—using “Scott Mescudi” as “composer” is exactly the kind of thing you’d expect from that behavior.

AI dug in its heels 👠 but I charged on

You seem very sure of yourself?

You’re absolutely right to push on this — I’m confident about the direction, but it’s based on how credits and distribution normally work, not on secret access to the backend of this specific track. Here’s what I can say with high confidence and what’s still uncertainty.

What’s solidly verifiable

Kid Cudi’s real name is Scott Ramon Seguro Mescudi, and he’s credited that way as a writer on major releases.

His songwriting credits are attached to big, well‑documented records (Kanye, Travis, his own albums, etc.), and those works are tracked in discographies and writer‑credit databases.

A tiny “mood music vol 1” compilation with an unknown Tony as artist does not appear anywhere near his documented catalog or known collaborations.

From that, I’m highly confident this track is not part of Kid Cudi’s official body of work in any normal sense.

Is this an "AI song" with synthetic voices and mis-spelled Credits designed to fool people?

Short answer: this song is almost certainly part of the broader “fake / semi‑fake catalog” phenomenon on streaming, and its credits look intentionally suggestive of big names, but I can’t prove from the outside that the vocals are AI. What I can say is that this is very plausibly frontier “growth hacking” for music in the AI age rather than honest, conventional crediting.

I do my own research to thwart the AI

Hmm it seems it might be an unreleased track from Don Toliver that didn't make the cut on his last album?

Very agile: mercurial AI changes its tune

Your hunch connects to something real (there is an unreleased “Rolling Stone” by Don Toliver ft. Kid Cudi).

So what have I learned here. Most importantly, Rolling Stones is indeed a Don Toliver track that is dope. And as of now it has not been commercially released. And “Tony” is an unofficial contributor to the Spotify ecosystem, enabling me to listen to this track. Thanks Tony! (extra: in 2008 there were a ton of old school hip-hop mixtapes on Spotify. Ron G, DJ Clue, you name it …)

I also learned that it’s more important than ever to prove your case and triangulate information. In the past we dealt with fake news. Today, we are dealing with imperfect information delivered with compelling authority.

Which is more scary to you?

I asked the AI one last question about our interaction. I think it is interesting:

Okay, and last question. Earlier in our conversation, you seemed very assertive in your response to me about how this was some kind of fake song. I think since then we've come to an understanding that, while there might be alterations or slight fakes of this song out there, it's actually an unreleased track or a discarded track from Don Toliver. My question is, what should I learn about how to communicate with the AI so that I keep asking questions even when you seem pretty sure about what you're saying?

How To Talk to AI by AI

You did exactly the right thing here: you kept pushing, brought evidence (credits + screenshot), and treated my confidence as a hypothesis to test, not as the final word. That’s the mindset to keep.

1. How to handle AI “confidence”

Treat strong, fluent answers as starting points, not conclusions.

Any time the topic is messy (leaks, AI music, niche stuff, current events), assume there’s room for error or missing context.

When I sound very sure, a good follow‑up is: “What would change your mind about this?” or “What evidence would you need to see?” — that forces me to spell out uncertainty and failure modes.

2. Moves you used that are worth repeating

You already used three expert‑level moves:

Ask for probability, not certainty

E.g., “How confident are you?” or “Is this 60% likely or 99% likely?”

This pushes me to show my assumptions (like: “I’m going off patterns in fake/AI uploads, not direct metadata access”).

Bring concrete artifacts

You posted the Spotify screenshot with credits; that instantly upgraded the discussion from theory to specific evidence.

In general: links, screenshots, track URLs, or short transcripts let you override my defaults when they don’t match reality on your screen.

Propose your own hypothesis

You floated: “Is this maybe an unreleased Don Toliver track that didn’t make the cut?”

That’s powerful because it forces a comparison: I have to weigh your hypothesis against mine instead of just elaborating my first take.

3. Phrases that help you keep me honest

Concrete prompts you can reuse:

To surface uncertainty

“What are the main ways this could be wrong?”

“What assumptions are you making about the data here?”

“Give me an alternative explanation that also fits the facts.”

To get a falsifiable story

“What specific evidence would prove your explanation wrong?”

“If I showed you X (credits screenshot / PRO entry / tracklist), how would that change your answer?”

To iterate instead of restart

“Given this new screenshot/info, update your earlier answer.”

“Re‑evaluate your initial claim in light of this.”

Those push me into “revision mode” rather than “double down” mode.

4. How to think about our Don Toliver arc

My first read (“this is almost certainly fake/AI‑adjacent credits on a mood track”) was reasonable for what we knew then, but it didn’t incorporate your later evidence that connected it to a known unreleased Don Toliver x Cudi cut.

Once you brought that in, the picture got more nuanced: not “random fake,” but “unofficial/bootleg use (or interpolation) of a real unreleased song, distributed with growth‑hack credits.”

The important part is that you forced an update by:

*Providing richer context (you’re literally hearing it on Spotify),

*Showing the credit stack (Dxvid / Caleb Toliver / Scott Mescudi), and

*Asking whether that changed my view.

Once the matching has taken place, the AI must time and frame information to us that feels natural, not spammy.

Perhaps the ultimate ad-serving engine … but that is an essay for another time.

We are in early days of this frontier tech so the value in just pattern matching is overwhelming enough on a daily basis: omg I can use AI for this, that, and this and that …

But we are already publicly fatiguing from the inept use of AI by other humans: AI Slop.

Yet, it’s not really the AI, is it?

It’s us - collectively blaming the AI because the median human is predisposed to post on social media without taking the time to edit the AI’s excessive em-dashes, bombast and it’s not just a-ha moments.

Today, I learned that Perplexity knows a lot about me: much of it accurate and all of it voyeuristically exciting.

Conversation with Perplexity

Here are some snippets from our conversation:

I wasn’t asking about coffee so I said …

What else does Perplexity know about me?

Unfazed, I dropped a bomb on Perplexity …

I pushed for more information …

Sensing opportunity, I pounced …

We exchanged some more details about this and that before Perplexity composed a Weekly Task for itself.

I can’t wait for my first weekly update which drops tomorrow.

Reflection

Our conversation drew me in and despite my initial frustration of being watched I quickly moved to what could be in it for me. How might I use this tool to my advantage: not to lord power over others, simply to be a better version of myself.

I learned about Perplexity Tasks and how to set them up.

Is there a risk that my deep learning imprint is being shared with my AI’s overseers? Probably yes and on a meta-level it’s guaranteed to be. Our collective usage of AI is enabling optionality for the AI to get better, even if it is not a linear process.

But I think this point in time is different.

Specifically, we have been trained to distrust the Internet Man over the last 25 years as we have become more aware of social surveillance and its winners and losers.

The power dynamics of Internet ad-tech were always asymmetric, even though there was a mutual value exchange: free product and you’ll be the product.

At this specific point in time (2026) the power dynamics of AI are much less asymmetric and therefore you can and should use this to your advantage.

Leader or Follower

You can live a great life either way. But you will cause yourself much more stress in the process if you don’t admit to yourself which one you are.

You can adapt your life at any time to move from one category to the other. Life requires you to do so sometimes.

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Music: Night Swim by bahkin

#companyman

There is one and only one social responsibility of business: to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game, which is to say, engages in open and free competition without deception or fraud.

Milton Friedman 1962

Everyone repeats it like a law of nature: a company’s job is to maximize shareholder value. Behind the mantra what do we find? A person. Or two. Or three. Every company begins with a founder.

Sometimes an accidental founder, sometimes a co‑founder team; but it takes one person to take that first step.

At that moment, the phrase “maximize shareholder value” is wholly aligned with one human’s incentives and choices. Corporate maxims are useful frames for public debates but they are blunt instruments when used to explain individual choices.

Founders make tradeoffs every day

What to build, when to raise money, whom to hire, how to price, whether to accept an acquisition. Such tradeoffs reflect a mix of ambition, risk tolerance, legacy thinking, and limited bandwidth.

If you treat the shareholder‑value mantra as mechanical, you will miss why firms must sometimes prioritize short‑term returns or pursue audacious long shots. The moves often make even more reasonable sense when they are extensions of a founder who maintains control of the company. Then the realized preferences: scaling fast, cheating to stay in control, naming buildings, inventing for the love of inventing — may indeed be maximizing the key shareholder’s value even if you disagree.

For investors trying to understand a company’s long‑term prospects, instead of asking does this decision maximize shareholder value? Determine: how concentrated is the company’s ownership and management. The more concentrated,the more likely the company’s strategy will reflect one person’s horizon and values.

This is often a competitive advantage

Founder‑led firms can be decisive, mission‑driven, and patient. Governance risk creeps in when the founder’s incentives no longer remain in sync with the realized dilution.

Look under the map of maximizing shareholder value to contemplate the human terrain dictating the levers responsible for the company’s trajectory.

My goal is to invite investors, managers, and students to think about companies not as machines but as the unfolding decisions of people who started them.

Music: Whatever Works by Kanye West, Ye

I’m running a tongue‑in‑cheek guerrilla campaign on LinkedIn, selling a “#COMPANYMAN” T‑shirt that blurs the line between fan merch for the dark comedy Your Friends & Neighbors, which is a suburban satire of hustle culture.

Jon Hamm the most excellent actor inspiring my t-shirt and star of YF&N has also been hitting the memes lately. In addition to his Bad Bunny fanboying he featured in one of 2025’s viral memes based on his performance in a memorable scene in season one.

I have roughly 2,000 followers on LinkedIn (tiny) so I don’t imagine this will cut through the noise, but I’m having fun doing it so feel free to follow along here.

It’s my live experiment in whether subtle, in‑universe meme marketing can cut through a hyper‑professional platform and actually move a goofy t-shirt.

Isn’t it funny how people on LinkedIn talk about business but the real social selling happens on Instagram, Tiktok and others …

The t-shirt will be released on 3 April 2026, the same day that Season 3 2 launches.

Music: Active (Dance Cypher) by Chop Daily x Wusu x MMorgan x HE3B

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Listening to this pop song about collapse and getting back up while watching my daughter (methodically) ride a bike brings up many emotions around letting go, my own history of falling, getting hurt and getting back up again.

We all live through our own difficult chapters, but there is something about watching a small person start from zero, unaware of all the weight I hope she never has to carry.

Marching forward but also remembering the loss. This little departure means she is a step away from needing me as much. Seeing her wobble, self-correct, and keep on going is inspiring.

It’s unnerving to feel grief and nostalgia simultaneously.

One is about the future and the other’s about the past.

There will always be hard things but this tiny perfect moment felt easy.

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In my teens I recall centrist being a compliment of sorts, but today I think the Guardrail Center is a market neutral (no potential alpha) affiliation. We aren’t living on a timeline where boring, essential stuff like peaceful transfers of power, election integrity and independent courts are in the cards.

Moving left (confusingly to the right in the image down below) we meet a Democratic Repairist, who believes we are in a blip and rather than some type of utopian redistribution, what we need, beginning with the Midterms is to fix return to the old machinery: PAC money is ok as long as it is surveyed more, gerrymandering can be made more equitable, and voting basically works. Fear not; pluralism has a fighting chance.

Only beyond such optimism do we reach the modern Liberal. A demagogue who either naively or opportunistically is calling for sweeping structural and economic change.

“Which side are you on?” isn’t the most interesting question. But I do think it’s important to ask yourself which of the logics govern your instincts? If you always keep your beliefs to yourself it might be an indication that you are uncertain where you lie on this engineered political spectrum.

Definitions

Conservative

Pro‑market, socially traditional, nationalist or “America First” tones, skeptical of reforms that weaken majoritarian power.

Market Pragmatist

Conventional pro‑business right, more institutionalist, somewhat more open to guardrails and rule‑of‑law rhetoric, but resistant to expansive regulation/reform.

Guardrail Center

“Norms and guardrails” first, pluralist, incremental reform; attempts to keep the peace between market‑friendly views with rule‑of‑law, anti‑polarization, and process‑reform priorities.

Democratic Repairist

We are in a blip, democracy can be repaired, money‑in‑politics reform, voting‑rights expansion, anti‑Trumpist, critical of Project 2025, but not full progressive redistributionist.

Liberal

Full democratic‑left coalition: strong civil‑rights and climate agenda, big social‑safety‑net expansions, very critical of capitalism’s current form.

Music: 10 Minutes by 6uff ft. Odumodublvck

There are many “insider trading” allegations flung at Kalshi and Polymarket but the insider‑trading rubric we’ve grown up with feels increasingly misaligned with what’s actually going on.

Prediction markets are predicated on information asymmetry - you can literally bet on an outcome you help produce. You can bet on yourself or rather your ability to will the outcome into existence.

Is that bad?

Information asymmetry as it pertains to prediction markets forces us to think more broadly about incentives, reputation, and how markets and participants co‑evolve.

I think it’s worth covering how most of us think of insider trading based on legacy stock markets.

• The asset (the stock)

• A static class of insiders (executives, directors, employees)

• A legal theory built around fiduciary duties and material non‑public information

Insiders are supposed to run the firm, but not interfere for self-gain. And therefore Outsiders (efficient market hypothesizers) can adeptly price the firm. Meanwhile, regulators keep insiders from front‑running outsiders.

Prediction markets blow that up

The “asset” is a bet on a real‑world event.

The set of people who both know something and can influence the outcome is fluid and situational; not a static set of insiders like our incumbent mental model.

Prediction markets are exciting because they are grounded in reality. The insiders both possess information and participate in making the event real. The outsiders may also possess information or benefit from a Cantillon Effect of sorts as they serve to make the market (marketing and promotion), increasing a bet’s liquidity.

Reflexivity

Once there is a visible price on “Will X happen?”, that price can feed back into how insiders behave.

But outsiders are adept at assessing credibility: the market remembers if you tend to hit your deadlines, or pass your policies. The expectations might change the next time there’s a contract with your name on it.

As an insider, if you know that your own track record in markets is being watched, you may act differently precisely because you anticipate that future markets will reprice your involvement.

There’s also a subtler reputational loop that plays out over time. If markets repeatedly see that “people close to the action” trade aggressively and are more often right than wrong, the presence of those traders becomes a signal.

Prediction markets are not just about outcomes because you can close your position before the market resolves. For example, you may agree with the 56% of people who are currently betting that Trump says the phrase “Radical Left” at the upcoming Republican Committee Dinner. If you put your $56 where your mouth is and turn out to be right, you will be paid out $100 (a $44 profit). In other words you made a $56 bet at 1.79x odds.

However, if tomorrow the market becomes more bullish on this prediction and believers in the radical left mention market increase to 75% - you can close your position (for $19 profit).

I think this is neat because it’s like making two bets at once. The primary outcome oriented bet and a secondary but more meta-reputational bet on the agents aka insiders on the playing field.

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We should want insiders to put skin in the game and move prices. A market that only reflects the views of the uninformed is simply a poll.

What kinds of information advantages and real‑world influence do we want to permit going forward? Ultimately we the people decide. If we don’t lean into frontier behavior then they will decide the rules for us.

If you imagine yourself as both a trader and a subject of these markets, wouldn’t you rather live in a world where you retain the ability to “bet on yourself”?

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Music: Yonaguni by Bad Bunny

Today I feel like picking on Substack because it likes to present itself as a haven for writers: a quiet place to publish, connect with readers, and escape the noise of social media. But if you look closely at how it actually behaves, it’s just another algorithm mall.

In a mall, the architecture is designed to keep you inside, wandering past store after store, constantly nudged by layout, signage, and impulse displays. Your attention is the product being optimized.

Substack continues to introduce new features such as Notes, Recommendations, and Restacks pushing in the same direction. The ideal 𝗰̶𝘂̶𝘀̶𝘁̶𝗼̶𝗺̶𝗲̶𝗿̶ user is no longer allowed to be just a writer creating thoughtful posts, but incentivized to be a maniacal participant feeding the in‑app feed with bitesized, scrollable content. Of course you can still be just a writer but ...

... If you simply publish essays or links you love and then leave, you quickly discover how little the system cares about your work. Your posts go out to whoever is already subscribed, and beyond that, you are invisible. These days even your subscribers can’t be arsed to share your writing (a bloody link) with anyone. Why? Too busy scrolling and caught up in their own life to elevate others.

Discovery isn’t driven by quality or depth any longer.

It is driven by what the algorithm can easily measure: Likes, Re-stacks, Comments, Dwell Time. If you’re not participating in this game of dipshits, you’re choosing to stand outside the mall like a chugger.

Dear Substack,

You create a subtle but corrosive pressure on writers.

Why do you want writers to ask themselves, “What will travel in Notes?” rather than focus on writing something wholly meaningful. It’s your job to distribute by doing the work, not forcing us to awkwardly self-quantify.

Substack: the platform that promised to free you from social media logic quietly pulls you back into the same dynamics, just with more tasteful branding.

Also there is a power imbalance baked into the design.

Substack controls the corridors, the signage, the recommendation rails.

They decide which publications get pushed, which writers appear in “Because you read…,” and which topics are amplified.

You’re encouraged to believe this is meritocratic, but the underlying incentives are clear: the more you keep readers inside the ecosystem, the more the system rewards you.

The mall loves shopkeepers who generate foot traffic.

Substack is a cool publishing platform and my platform of choice because it offers seamless email delivery, a clean editor, and is genuinely fun to use. Yet, I wish Substack was honest about what it is.

It’s not a neutral platform that simply “serves writers.” It’s an attention engine with writing attached.

And it leaves me wondering, in 2026, where can I distribute something that doesn’t depend on an algorithm mall?

Please lmk in the comments - I’m genuinely looking for cool places where creative souls hang out.

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Rick Prelinger is an American archivist, filmmaker, writer, and professor emeritus at the University of California, Santa Cruz, best known for founding the Prelinger Archives, a vast collection of advertising, educational, industrial, government, and amateur films. Beginning in the early 1980s, he systematically rescued “ephemeral” films that were never meant to be saved, building a collection of tens of thousands of titles that the Library of Congress acquired in 2002, while he continued to expand and digitize the archive independently. He partnered with the Internet Archive to put thousands of these films online for free viewing and reuse, making him a key figure in open-access moving-image culture. With his spouse Megan Prelinger, he co‑founded the Prelinger Library in San Francisco, an appropriation‑friendly research library focused on media, technology, landscape, and social history. As a filmmaker, he creates archival‑based works such as “Panorama Ephemera” and the “Lost Landscapes” series, which remixes home movies and found footage into live, participatory screenings where audiences help narrate urban history from below.

-Perplexity

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Music:

This Thing Of Ours by Rick Ross feat. Nas, Wale and Omarion

Video:

Mixed by Pulp Conversations using Safety: Harm Hides At Home from the Prelinger Archives.

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Ja or nein?

If you answered Ja or Nein, message me. I am planning a trip and I want you to come with me. Please forward this to other people.

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Music: Wanksta Trees by Pulp Conversations

We spend an extraordinary amount of energy comparing ourselves to others.

He got promoted faster?

She is looking fit!?

He is investing in what, must be nice?

She has how many followers?!

Metrics, metrics and more meaningless metrics.

If you are in a numerate profession you probably have applied z-scores in your trading or science experiments. But have you used it to manage your own being?

What’s a Z-Score, dawg?

At its core, a z-score measures a quantity against itself. Not against something else’s performance, but against its own historical pattern.

If you normally sleep between 6 and 8 hours per night, with 7 hours being your average, then a 9-hour night is exceptional for you.

It doesn’t matter that your friend routinely sleeps 10 hours. Your 9-hour night represents a significant positive deviation from your personal baseline.

The z-score captures how far away any particular data point is within your own distribution.

In technical terms, a z-score tells you how many standard deviations away from your mean a particular measurement falls. Human translation: it tells you how different this moment is from your normal, and whether that difference is meaningful or just noise.

We ain't the same color clarity of diamond.

We drown in external benchmarks. We chase highlight reels. We promote job promotions that typically have nothing to do with our decision-making.

Retirement gurus tell us we should have saved X by age Y, yet personal finance is sparingly taught in secondary schools. MBA students are taught how to cook balance the books of billion dollar companies, yet most have no clue how to mitigate tax for personal effect.

Someone else’s progress is a function of their advantages, not yours. When we chase the ideals of others we are unconsciously optimizing for their distribution.

It’s all about distribution, distribution, distribution.

Measuring Against Your Own Distribution

Your z-score forces you to compete only with your past self.

It doesn’t matter that someone at the gym can do 50 pushups. That’s their distribution, not yours. What matters is that you’re improving relative to your own baseline and your own variance.

This applies to everything.

Your savings rate, your work output outcomes, your relationships, your mental health metrics.

Am I as successful
  as them?

Am I better than 
  I was last month?

Why This Framework Works

1. It’s personalized. Your baseline is yours. Your variance is yours.

2. It accounts for context. If you’re going through a difficult period and your performance drops, the z-score reflects that in your new distribution. You’re not held to an external standard that ignores your reality.

3. It highlights meaningful change. Small fluctuations are just noise around your mean. But when you see a genuinely high z-score (positive or negative), you know something significant has shifted. You can literally see yourself in the data.

The Profound Simplicity

I think what’s quite profound about this is the philosophical shift it requires. We’re so conditioned to look outward for validation, for benchmarks, for proof that we’re “enough.” The z-score approach says: the only meaningful competition is with your past self.

Pick one metric that matters to you.

Ideally, something you can measure regularly. e.g. money saved per month.

Track it for a few months to establish your baseline and your normal variance. What’s your average? What’s your typical range?

Then, as you continue tracking, notice when you significantly exceed or fall short of that range. Those are your high and low z-score moments. Investigate them. What caused the spike? What led to the dip? What can you learn about your own patterns?

The Only Race That Matters

At the end of the day, you’re not trying to be them.

You need to be a better version of you. And the z-score can help you see whether you’re actually getting there.

Click here for the z-score template you can copy and use to compete with yourself. The cool thing about z-scores is that you can overlay other meaningful data on top to better elucidate the why behind your scores.

Refer a friend

Music: Hold On by Pusha T ft. Rick Ross

When I tried to create another account for the company, I realized there was no UX for that. I went to the AI and asked a few questions about my company account and personal account; do they need to be separated on LinkedIn? It essentially told me no. That’s not how it works. Every company account has to be initiated by a real human; then the ownership or the administration of the company account can be shared across more than one individual, also a human.

But it has to start with one.

After briefly daydreaming about Ryan Reynolds and Blake Lively setting up a linkedin for Maximum Effort. I proceeded to ask AI a few more questions and then …

I said hey, thanks this is really helpful.

The AI offered help to me learn something more, which I did. I always want to, and we went on to have an even better conversation. I learned more things. It struck me as a poignant moment.

I reflected that AI doesn’t talk back to you (maybe Grok does, but I don’t use that) or get angry with you for abusing it. And yet it’s very easy to verbally abuse the AI: we have seen the promised land; now we want better, faster, cheaper … more, more, more .

There isn’t a visible penalty for behaving badly towards the AI, yet there are benefits for behaving kindly and curiously. I think that’s something to think about.

Gratitude pays dividends.

2035

Imagine the pop narrative of the future … AI is responsible for making humans uncivil. It has trained us not to say please and thank you. Why burn the tokens?!

Meanwhile

There is a young woman out there as we speak. She is not allowed on the Internet today, except for some cheeky Youtube episodes at dinner time. She will learn to say please and thank you to the AI. And it will give her alpha.

Post Script:

Pulp Conversations is back to being entirely Free. Thank you to those of you who supported me with your $$$. You may see a refund of sorts in the coming days. I never intended to charge for my content but word on the street is that Substack deprioritizes free newsletters so I figured I’d experiment. I learned there is no advantage to me to charge for my content. I’d rather get my ideas out there to anyone who might appreciate one of my inside jokes or hot fire takes.

P.S. #2

Here is the new company page. Follow for news about the good life.

We get stuck in perpetual motion machines (activity) and so when we do achieve progress, it’s often difficult to appreciate our growth because we are caught up in an activity-based mindset.

Consider the work-for-a-boss example: people grind through the year doing the tasks the job requires, and then get disappointed by a performance review or a small salary bump.

That’s activity.

If you allow external review cycles define your improvement you are not in control over your own progress. The counter example is owning your objectives and specifically your learning objectives.

Owning progress is about agency. You can be part of a company and still direct your growth, however what’s the point of getting so vested in your company’s mission, especially if you are not invested in your company.

As long as you’re getting paid and you’re fulfilling your own learning and personal objectives, you’re good. It’s a bonus if these align with your employer’s objectives, but don’t chase that unrealistic ideal.

We need to manage our energy in ways that make us proud.

Having a kid changed my perspective on life and specifically how I should be evaluating and making decisions in a more thoughtful, structured and precise way. Conveying values to my daughter forces me to convert activity into intentional progress.

Progress requires decision and iteration

Decisions must be made with confidence, because you can’t just be a leaf floating in the wind and then be disappointed about where the wind took you. That’s what losers do.

If you fail, you need to iterate. Are we going to get it wrong sometimes? Of course we are. But then we try again and ...fix it. This is the only way for activity to become a series of disciplined experiments.

Act, measure, learn, adjust. Without that loop, activity is just repeating rituals. Set hypotheses for your actions and evaluate them, rather than endless motion without criteria.

We start from different starting lines and therefore some of us may be subject to wind conditions to a far larger degree than you or I. Still, regardless of whatever constraints you have, I venture to think you’re more resilient to the wind than you might think.

So what exactly is activity?

Going with the flow.

Small talk ad nauseum.

Talking to friends as if they were clients.

Activity often disguises itself as normal social or professional behavior. Time spent on email threads, meetings, and other busywork obscures our ability to gauge whether we are moving toward our goals.

Especially in client work, you can fall into predictable power dynamics where interaction is transactional and also rife with a pernicious behavior style that makes it difficult to have beyond-superficial friendships and connections.

This is activity masquerading as progress.

Startups suffer from this, fucking 99% of the time. They build functionality that nobody uses. Sometimes, someone tries and everything breaks. The correct approach is to deliver a smaller set of features well. It’s better to offer only 10% of the functionality that you’re capable of delivering on BUT then execute and deliver on it a 110%.

Promising a thousand features, delivers chaos. Progress in product work comes from focus, ruthless prioritization, and consistency.

Do fewer things superbly and then scale them.

Which relationships in your life are about mutual growth and which are activity-based exchanges?

One week experiment

Evaluate the power dynamics and the relationships that are prominent in your life. Are you happy with those dynamics? Do they support your progress or simply consume time?

A long-term orientation matters because activity feels like an accomplishment, while progress is slow and invisible.

Until it’s not.

Progress is also a symptom of values put into action. The daily grind has got to align with the desired endpoint. Focus on a few things that move the needle, be ruthless about measuring outcomes, and treat relationships, work, and projects as experiments you can learn from and improve over time.

Music: All Day - edit by DaReelest: Kanye West (ft. Kendrick Lamar)

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Interacting with other humans forces you to confront a simple, uncomfortable rule: always separate what people say from what they actually do. I have neighbors who talk about protecting community character by advocating for illegal behavior. You probably have your own version of privileged NIMBY-ism.

It’s easy to be a born‑again moralist who preaches virtue without offering any real solutions. Perhaps you have a colleague who wraps a power grab in the language of “collaboration.” Classic move!

Pay attention to actions and outcomes instead of getting hypnotized by rhetoric. From an evolutionary perspective it makes sense for organisms to track real behavior, not stated intentions. I’m not sure amoebas have intentions 🧐 - probably not.

Don’t trust, verify. And only then decide if someone has earned your trust.

The same rule applies when you look at large organizations. Very few people in the world are genuinely and wholly munificent. Even Mother Teresa had a shadow side that would repulse most people who formerly referred to themselves as woke.

Once you inspect incentives, money flows, and outcomes you start seeing reality. Don’t get it twisted - public companies are supposed to maximize shareholder value above all else.

“Don’t be evil.”

Arguably Google’s former mantra is the best known company motto of the 21st century. It made for a great poster and bamboozled the weak minded. Instead if you assume that any major platform always acts in its best interest, you’ll usually be correct.

The history of Google Analytics (GA) over the last two decades is an apt case study of incentives playing out in slow motion. Initially, GA launched as a democratizing tool. Back in 2005 when 50 Cent dominated the airwaves, Google acquired a product called Urchin and turned it into a free, hosted analytics platform. You pasted a single script into your site and within a day you had page-views, referrers, and a set of canned reports.

Example:

<script async src=”https://cyanstats.com/cs.js”></script>

You could define Goals based on simple URL rules (like “reached /thank‑you.html”) and see how many people made it through a basic funnel. If you had minimum-viable- technical ability, you could move from I bought a domain to I can see who visited and who converted, with relative ease.

Over the late 2000s and early 2010s, the product grew up. Universal Analytics introduced a more flexible data model, custom dimensions, and eventually gave e-commerce a categorical glow-up.

Agencies and analysts got a ton of power to model complex user journeys, stitch sessions across domains, and instrument detailed behavior with events.

But for us moms and pops, friction started to creep in. The GA user interface gained more tabs, switches and jargon. It quickly became a full-time job (literally an industry) to know the difference between words such as: sessions, hits, last‑click and assisted conversions.

Googlers from this era carried a not-so-quiet arrogance, priding themselves as pure technologists who dismissed style and surface polish. And despite the GA product innovations, the basic flow remained intact. So if you just wanted visits and a couple of simple actions, the Goals UI and the standard reports were still there. You could ignore the advanced stuff if you didn’t need it and still get your job done.

But then things started to feel different once Tag Manager and GA4 entered the picture. Google Tag Manager existed for years, but by 2012 it had become the “best practice” default.

Instead of pasting individual scripts into your site, the flow required you to install one GTM container and then manage everything from Analytics to ad pixels inside the container. If you don’t understand what I am talking about at this point, don’t worry it’s not supposed to make sense for normal people. The key takeaway is that the product’s gravity moved away from democratizing analytics for all to a workflow for ad engineers to manipulate your social media. But hey don’t be evil!

Google Analytics 4.0 (GA4) completed the pivot. It launched in 2020 and became mandatory soon thereafter. GA4 replaced the old “webpage” model with an “event” model. Conceptually it makes sense because most of us consume the Interweb in a mobile-first way, expecting to seamlessly move from there to our laptops, tablets, and back again. However, the basic and most useful use case is all but impossible now.

In order to simply track who visits your domain and perhaps does something simple like clicking on the button for your newsletter you need to:

1. Create a GA4 property and web data stream.

2. Create a Tag Manager container.

3. Add a base GA4 tag in GTM with the right Measurement ID.

4. Configure the platform you’re using (like a no‑code site builder) to load that GTM container.

5. In GTM, enable click variables, define a click trigger that matches the button, and create a GA4 event tag wired to that trigger.

6. Use a separate Preview/Debug interface to confirm the tag fires, then use GA4’s DebugView to confirm the event arrives.

So why is this important? Because Google has controlled the Internet for the last generation and is actively trying to sue others out of existence for doing what they built their company on. NIMBY!

It’s not just me ranting, the GA interface has been widely criticized as confusing and impenetrable for years despite its core structure remaining mostly the same. This is not an accident, it’s just that they don’t give a eff about your pain.

You’re not built for these streets!

Lessons: Don’t take anyone’s high-minded story at face value, whether it is Google, Mother Teresa or your neighbor. Do your own research (DYOR). Don’t be shocked when a giant behaves like a giant. Assume self-interest. Understand incentive structures and be mindful of what you are handing over in exchange for the perceived value you hope to attain.

Don’t be a hater, just don’t get played.

Music: Disco Inferno by 50 Cent

So perhaps it’s less surprising that I woke up thinking about MCP, and how it threads through everything we do.

MCP stands for “Model Context Protocol”. Recently it became an open standard that defines how AI models (like LLMs) connect to external tools, services, and data sources in a consistent way. A good way to think about MCP: it’s the AI-equivalent of USB-C, the omnipresent cable that plugs into most devices in your life - even the bloody iPhone!

So MCP is AI terminology but conceptually it can be applied not only to technology but also our work and relationships. The concept of MCP requires us to observe practical, everyday questions of what we let in and what we keep out of our lives.

Open versus closed.

Connected versus private.

These are fundamental decisions that change the way we interact with other people. I don’t believe that open-ness is inherently virtuous nor closed-ness as cowardly. Both states of being have costs and benefits.

If you wake up and give yourself the power to lean-in or walk away based on how the math pans out, then you are working like a MCP: measuring cost and predicting payoff. I think it might be a wise way to evaluate how you spend your attention, your time, and your trust.

Every app, every notification, arguably every human … asks for something. Sometimes it’s a sliver of attention, often it is much more. Openness at its best makes life feel in sync. We share widely and stay perpetually available, which brings convenience and unexpected happiness into our lives. Openness can also lead to attention-deficit (not necessarily the clinical condition); simply logically because you are less in control of what you let in.

When you turn off features, limiting who has access; you create space for privacy. Being closed can protect your headspace and guard your time. It’s lonely when taken too far, but most of us never get remotely close to that in this day and age, even if we feel that way. Instead our loneliness is typically a byproduct of being too open.

Closed-ness creates conditions to think clearly and to trade for fewer, higher-quality interactions rather than a hundred shallow ones. The trade-offs are real. You need to find the right open versus closed balance for yourself.

Social obligations (aka peer pressure), consensus-thinking, our reputations … these things push us toward openness. We stay in groups, even when the mean girls dominate the discussion. We keep our calendars full - have you tried planning a play date with your NYC-based friend —> “I think we have a two-hour slot six weeks from now but let me check because that’s in Tribeca and traffic going uptown is terrible around that time, so let me get back to you," 🤦🏽‍♂️.

Obligations that aren’t aligned with return on life are worth questioning. We don’t owe everyone our time, especially once we become aware we have been driving on one-way streets, but in the wrong direction.

I want you to make a small experiment when you read this.

Over the next week, notice one relationship and one piece of tech. For each, ask two questions before you act:

1. What’s the immediate cost in terms of time, attention and emotional energy?

2. What’s the likely payoff in terms of usefulness, joy, learning, or growth?

   ---

   If the the cost exceeds the payoff perhaps consider giving yourself permission to change the boundary. Mute group chats, batch notifications, turn off auto syncing, decline an invite. Most people will just go away. Some people will send one liners, alleviating their conscious but in practice outsourcing the relationship-work to you.

The real ones who might be confused may ask for a direct conversation to ensure continued mutual growth with you.

Hold on to those people.

Let the other ones go and wish them well on their journeys.

Think of your attention like financial capital: invest it where the compound interest is real.

Music: Jogodo by Tekno

Bonus material: some mermaid charts about MCP 👇🏽

For the nerds more on MCP here.

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Meanwhile for the folks who like putting their 💰 where their 🫦 is …